Academic literature on the topic 'Revenue'
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Journal articles on the topic "Revenue"
Chambon, Jean-Pierre, and Andrea Castro Quintana. "Les types toponymiques oïliques Revenue, Revenu, et frm. revenue, terme de sylviculture." Nouvelle revue d'onomastique 61, no. 1 (2019): 69–78. http://dx.doi.org/10.3406/onoma.2019.1909.
Full textTAIROVA, Svetlana S. "Non-tax revenue planning." Finance and Credit 28, no. 3 (March 30, 2022): 528–56. http://dx.doi.org/10.24891/fc.28.3.528.
Full textRaifu, Isiaka Akande, and Abiodun Najeem Raheem. "Do Government Revenues Matter for Economic Growth? Evidence from Nigeria." European Journal of Government and Economics 7, no. 1 (June 27, 2018): 60. http://dx.doi.org/10.17979/ejge.2018.7.1.4333.
Full textGunawan, Edy. "Tax Court Decisions as the Ultimum Remedium for Taxpayers." Law Review 22, no. 3 (March 29, 2023): 289. http://dx.doi.org/10.19166/lr.v22i3.6319.
Full textRustendi, Endi. "ANALISIS EFEKTIVITAS, EFESIENSI DAN KONTRIBUSI PENERIMAAN PAJAK DAERAH TERHADAP PENDAPATAN ASLI DAERAH TAHUN 2010-2016." JRAK: Jurnal Riset Akuntansi dan Komputerisasi Akuntansi 9, no. 2 (August 20, 2018): 181–203. http://dx.doi.org/10.33558/jrak.v9i2.1588.
Full textSitumorang, Dokman Marulitua, and Faisal Jamaludin Al-Afgani. "Implementation of System Digitalization in Payment and Deposit of Non-Tax Revenue from Minerals and Coal Resources." Journal of Applied Management Research 3, no. 1 (June 28, 2023): 42–50. http://dx.doi.org/10.36441/jamr.v3i1.1546.
Full textMeyers, Daniel E., Benjamin S. Meyers, Timothy M. Chisamore, Kristin Wright, Bishal Gyawali, Vinay Prasad, Richard Sullivan, and Christopher M. Booth. "Temporal trends in oncology drug revenue among the world’s major pharmaceutical companies: A 2010-2019 cohort study." Journal of Clinical Oncology 39, no. 15_suppl (May 20, 2021): 6505. http://dx.doi.org/10.1200/jco.2021.39.15_suppl.6505.
Full textPhipps, Erin Hazel, Mark W. Nichols, and Federico Guerrero. "The Impact of Video Gaming Terminals on Casinos and State and Local Tax Revenue." Public Finance Review 48, no. 5 (September 2020): 650–75. http://dx.doi.org/10.1177/1091142120945684.
Full textAwotomilusi, Niyi, Oluwayomi Oso, Oluyinka OLUWAGBADE, and Muyiwa Dagunduro. "Evaluating the Effectiveness of IPSAS 23 Regulations on the Redemption of Tax Revenues by the Ekiti State Government." Journal of Accounting and Finance Management 4, no. 5 (December 27, 2023): 385–99. http://dx.doi.org/10.38035/jafm.v4i5.272.
Full textWantoch-Rekowski, Jacek, and Małgorzata Cilak. "The share of corporate income tax as revenue of a provincial self-government and the effects of the COVID-19 pandemic." Ekonomia i Prawo 20, no. 2 (June 30, 2021): 439–56. http://dx.doi.org/10.12775/eip.2021.027.
Full textDissertations / Theses on the topic "Revenue"
Berestovska, Yu. "Analysis of tax revenues as the basis of budget revenue." Master's thesis, Сумський державний університет, 2020. https://essuir.sumdu.edu.ua/handle/123456789/81809.
Full textFreeman, Michelle S. "Revenue Recognition." Digital Commons @ East Tennessee State University, 2018. https://dc.etsu.edu/etsu-works/5777.
Full textZickus, Jeffrey S. (Jeffrey Stuart) 1973. "Forecasting for airline network revenue management : revenue and competitive impacts." Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/10103.
Full textShioda, Romy 1977. "Restaurant revenue management." Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/28250.
Full textIncludes bibliographical references (p. 59-60).
We develop two classes of optimization models in order to maximize revenue in a restaurant, while controlling average waiting time as well as perceived fairness, that may violate the first-come-first-serve (FCFS) rule. In the first class of models, we use integer programming, stochastic programming and approximate dynamic programming methods to decide dynamically when, if at all, to seat an incoming party during the day of operation of a restaurant that does not accept reservations. In a computational study with simulated data, we show that optimization based methods enhance revenle relative to the industry practice of FCFS by 0.11% to 2.22% for low load factors, by 0.16% to 2.96% for medium load factors, and by 7.65% to 13.13% for high load factors, without increasing and occasionally decreasing waiting times compared to FCFS. The second class of models addresses reservations. We propose a two step procedure: use a stochastic gradient algorithm to decide a priori how many reservations to accept for a future time and then use approximate dynamic programming methods to decide dynamically when, if at all, to seat an incoming party during the day of operation. In a computational study involving real data from an Atlanta restaurant, the reservation model improves revenue relative to FCFS by 3.5% for low load factors and 7.3% for high load factors.
by Romy Shioda.
S.M.
Dobler, Michael. "Rethinking revenue recognition." Inderscience Publishers, 2008. https://tud.qucosa.de/id/qucosa%3A36452.
Full textHao, Eric (Eric C. ). "Ancillary revenues in the airline industry : impacts on revenue management and distribution systems." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/89854.
Full textThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 109-110).
Airlines have increasingly depended on ancillary revenue in response to rising fuel costs, de- creased yields, and an increasingly competitive environment. Estimates indicate that U.S. airlines collected over $8 billion in ancillary revenue in 2012. Ancillary revenue poses challenges for airlines, including revenue management (RM) and distribution since total revenue maximization requires consideration of ancillary revenue and ticket revenue. In this thesis, we: (1) describe trends contributing to the movement towards ancillary revenue; (2) present three methods for incorporating ancillary revenue into revenue management and distribution; (3) evaluate the revenue performance of these methods using the Passenger Origin Destination Simulator (PODS), a competitive airline simulator. One method of including ancillary revenue into RM is RM Input Adjustment with Class Level Estimates, which involves modifying input fares to the optimizer. Because fare values to the optimizer are aggregated by market and class, the airline uses class level estimates of ancillary revenue potential to augment fares. Another method involves modifying the fare value at the time of availability control, or Availability Fare Adjustment. In network optimization, the availability fare refers to the fare used to compare an itinerary-class to the control mechanism, like displacement adjusted virtual nesting (DAVN) or additive bid price (ProBP). Availability Fare Adjustment with Class Level Estimates also involves using class level estimates of ancillary revenue. Alternatively, we test scenarios where the airline estimates ancillary revenue for individual passengers in Customized Availability Fare Adjustment with Passenger Specific Estimates. Although this type of estimation is not feasible yet, results from Customized Availability Adjustment give a theoretical bound to revenue gain. We nd that incorporating ancillary revenue opens availability for lower yield passengers. Revenue increases occur from extra bookings in these classes because more bookings are taken. Revenue losses occur from higher class passengers buying down to cheaper seats. Without willingness to pay (WTP) forecasting, net revenue losses of up to {2.6% are observed. In advanced RM systems with WTP forecasting, revenue gains of +0.6% are observed for Class Level RM Input Adjustment, +0.9% for Class Level Availability Fare Adjustment, and +2.6% for Passenger Specific Customized Availability Adjustment.
by Eric Hao.
S.M. in Transportation
Leuhusen, Fredrik Carl Axel Peter. "Why Revenue Diversification Matters." Thesis, University of Pennsylvania, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10286178.
Full textRevenue diversification is a term that becomes more relevant as higher education institutions are confronted with increased regulation, competition, declining enrollments, and strained finances. A challenge that many institutions face is that expenditures are higher than revenues and increase faster than them. The term Revenue diversification seems obvious to higher education administration professionals, although they do not all define it the same way. For that reason, it needs a precise definition so that the industry genuinely can embrace the concept and thereby seek to generate more revenues to drive existing and innovative agendas. Indeed, a common understanding will allow universities to develop strategies to reduce the reliance on traditional tuition and fees. The study examines three not-for-profit institutions with a student population less than 5,000 that already are diversifying their revenue streams. The definition of leadership at each institution is compared with the strategies that have been implemented or proposed in order to understand whether there is alignment. The three cases—Stevenson University, Franklin & Marshall College, and Oglethorpe University—respectively have the following story lines: 1) growth is the only possibility; 2) the current situation is one of stasis, and the way forward is unclear; 3) efforts must be undertaken to improve financial viability. In addition to the qualitative research, the study also encompasses an analysis of IPEDS that reflects how each institution is changing its revenues in comparison to a similarly situated group of institutions. The findings reveal that Revenue diversification is on everybody’s mind, but the definition of the term is inconclusive. Leadership teams are trying to determine what revenue-diversification strategies will work for the institutions and its stakeholders to be able to offset expense increases. Identifying new revenue sources will entail pursuing non-historical revenue sources, which includes academic programs, services, property, institutional advancement, and more. The higher education environment is concerning to many of its member institutions, and by diversifying revenues, long-term viability can be secured.
Ciocan, Dragos Florin. "High dimensional revenue management." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/108211.
Full textCataloged from PDF version of thesis.
Includes bibliographical references (pages 149-153).
We present potential solutions to several problems that arise in making revenue management (RM) practical for online advertising and related modern applications. Principally, RM solutions for these problems must contend with (i) highly volatile demand processes that are hard to forecast, and (ii) massive scale that makes even basic optimization problems challenging. Our solutions to these problems are interesting in their own right in the areas of stochastic optimization, high dimensional learning and distributed optimization. In the first part of the thesis, we propose a model predictive control approach to combat volatile demand. This approach is conceptually simple, uses available demand data in a natural way, and, most importantly, can be shown to generate significant revenue advantages on real-world data from ad networks. Under mild restrictions, we prove that our algorithm achieves uniform relative performance guarantees vis-a-vis a clairvoyant in the face of arbitrary volatility, while simultaneously being optimal in the event that volatility is negligible. This is the first result of its kind for model predictive control. While our approach above is effective at hedging demand shocks that occur over "large" time horizons, it relies on the ability to estimate snapshots of the prevailing demand distribution over "short" time horizons. The second part of the thesis deals with learning the extremely high dimensional demand distributions that are typical in display advertising applications. This work exploits the special structure of the display advertising version of the NRM problem to achieve a sample complexity that scales gracefully in the dimensions of the problem. The third part of the thesis focuses on the problem of solving terabyte sized LPs on an hourly basis given a distributed computational infrastructure; solving these massive LPs is the computational primitive required to make our model predictive control approach practical. Here we design a linear optimization algorithm that fits a paradigm for distributed computation referred to as 'Map-Reduce'. An implementation of our solver in a shared memory environment where we can benchmark against solvers such as CPLEX shows that the algorithm outperforms those solvers on the types of LPs that an ad network would have to solve in practice.
by Dragos Florin Ciocan.
Ph. D.
Uichanco, Joline Ann Villaranda. "Data-driven revenue management." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/41728.
Full textIncludes bibliographical references (p. 125-127).
In this thesis, we consider the classical newsvendor model and various important extensions. We do not assume that the demand distribution is known, rather the only information available is a set of independent samples drawn from the demand distribution. In particular, the variants of the model we consider are: the classical profit-maximization newsvendor model, the risk-averse newsvendor model and the price-setting newsvendor model. If the explicit demand distribution is known, then the exact solutions to these models can be found either analytically or numerically via simulation methods. However, in most real-life settings, the demand distribution is not available, and usually there is only historical demand data from past periods. Thus, data-driven approaches are appealing in solving these problems. In this thesis, we evaluate the theoretical and empirical performance of nonparametric and parametric approaches for solving the variants of the newsvendor model assuming partial information on the distribution. For the classical profit-maximization newsvendor model and the risk-averse newsvendor model we describe general non-parametric approaches that do not make any prior assumption on the true demand distribution. We extend and significantly improve previous theoretical bounds on the number of samples required to guarantee with high probability that the data-driven approach provides a near-optimal solution. By near-optimal we mean that the approximate solution performs arbitrarily close to the optimal solution that is computed with respect to the true demand distributions.
(cont.) For the price-setting newsvendor problem, we analyze a previously proposed simulation-based approach for a linear-additive demand model, and again derive bounds on the number of samples required to ensure that the simulation-based approach provides a near-optimal solution. We also perform computational experiments to analyze the empirical performance of these data-driven approaches.
by Joline Ann Villaranda Uichanco.
S.M.
Veselová, Erika. "Modely sieťového revenue manažmentu." Master's thesis, Vysoká škola ekonomická v Praze, 2012. http://www.nusl.cz/ntk/nusl-165297.
Full textBooks on the topic "Revenue"
Yeoman, Ian, and Una McMahon-Beattie, eds. Revenue Management. London: Palgrave Macmillan UK, 2011. http://dx.doi.org/10.1057/9780230294776.
Full textFandel, Günter, and Hans Botho von Portatius, eds. Revenue Management. Wiesbaden: Gabler Verlag, 2005. http://dx.doi.org/10.1007/978-3-663-11304-1.
Full textBritain), Accounting Standards Board (Great. Revenue recognition. London: Accounting Standards Board, 2001.
Find full textDepartment, Fife (Scotland) Finance. Revenue budget. Glenrothes: Fife Council, 1998.
Find full textCouncil, Lambeth London Borough. Revenue estimates. London: London Borough of Lambeth, 1991.
Find full textPrice, Jeffrey W. Revenue law. London: University of London, 1992.
Find full textStuart-Buttle, Elizabeth. Revenue law. Guildford: College of Law, 1991.
Find full textOffice, General Accounting. Revenue options. Washington, D.C: U.S. General Accounting Office, 1988.
Find full textTutors, Holborn Law, ed. Revenue law. London: Holborn Law Tutors, 1985.
Find full textRamjohn, Mohamed. Revenue law. London: Cavendish Publishing, 1994.
Find full textBook chapters on the topic "Revenue"
Wagner, John E. "Revenue." In Forestry Economics, 125–49. 2nd ed. London: Routledge, 2023. http://dx.doi.org/10.4324/9781315678719-4.
Full textRoss, Justin M., and Denvil R. Duncan. "Revenue." In Teaching Public Budgeting and Finance, 30–50. New York: Routledge, 2021. http://dx.doi.org/10.4324/9781003240440-3.
Full textKimms, Alf, and Robert Klein. "Revenue Management im Branchenvergleich." In Revenue Management, 1–30. Wiesbaden: Gabler Verlag, 2005. http://dx.doi.org/10.1007/978-3-663-11304-1_1.
Full textCorsten, Hans, and Ralf Gössinger. "Kapazitätssteuerung im Revenue Management." In Revenue Management, 31–52. Wiesbaden: Gabler Verlag, 2005. http://dx.doi.org/10.1007/978-3-663-11304-1_2.
Full textSpann, Martin, Joachim Klein, Karim Makhlouf, and Martin Bernhardt. "Interaktive Preismaßnahmen bei Low-Cost-Fluglinien." In Revenue Management, 53–78. Wiesbaden: Gabler Verlag, 2005. http://dx.doi.org/10.1007/978-3-663-11304-1_3.
Full textOymann, Bernhard, Peter Schumann, and Bernhard Fleischmann. "Standardisierte Logistikprodukte für globale Belieferungsnetze." In Revenue Management, 79–100. Wiesbaden: Gabler Verlag, 2005. http://dx.doi.org/10.1007/978-3-663-11304-1_4.
Full textLindenmeier, Jörg, and Dieter K. Tscheulin. "Kundenzufriedenheitsrelevante Effekte der Überbuchung im Rahmen des Revenue-Managements." In Revenue Management, 101–23. Wiesbaden: Gabler Verlag, 2005. http://dx.doi.org/10.1007/978-3-663-11304-1_5.
Full textYeoman, Ian, and Una McMahon-Beattie. "Introduction: How to do it?" In Revenue Management, 1–5. London: Palgrave Macmillan UK, 2011. http://dx.doi.org/10.1057/9780230294776_1.
Full textHigbie, Jon A. "B2B Price Optimization Analytics." In Revenue Management, 120–35. London: Palgrave Macmillan UK, 2011. http://dx.doi.org/10.1057/9780230294776_10.
Full textZhang, Michael. "Fencing in the Practice of Revenue Management." In Revenue Management, 136–49. London: Palgrave Macmillan UK, 2011. http://dx.doi.org/10.1057/9780230294776_11.
Full textConference papers on the topic "Revenue"
Worsham, Elizabeth K., Alexander D. Thomas, and Stephen D. Terry. "Revenue Maximization for a Groundwater Desalination Plant and Small Modular Reactor Coupling." In ASME 2019 Power Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/power2019-1823.
Full textDughmi, Shaddin, Tim Roughgarden, and Mukund Sundararajan. "Revenue submodularity." In the tenth ACM conference. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1566374.1566409.
Full textPavić, Ivana, Ivana Mamić Sačer, and Lajoš Žager. "Challenges, Advantages and Disadvantages in Implementation of Ifrs 15 in Different Industries." In 2nd International Conference on Business, Management and Finance. Acavent, 2019. http://dx.doi.org/10.33422/2nd.icbmf.2019.11.769.
Full textLoRe, Anthony, Paul Stoller, and Robert Hauser. "Maximizing Energy Revenues: Providing the Best Incentive to the Contract Operator." In 14th Annual North American Waste-to-Energy Conference. ASMEDC, 2006. http://dx.doi.org/10.1115/nawtec14-3184.
Full textMehmood, Haleema, Madeleine Udell, and John Cioffi. "Revenue Maximization for Broadband Service Providers Using Revenue Capacity." In GLOBECOM 2015 - 2015 IEEE Global Communications Conference. IEEE, 2014. http://dx.doi.org/10.1109/glocom.2014.7417861.
Full textMehmood, Haleema, Madeleine Udell, and John Cioffi. "Revenue Maximization for Broadband Service Providers Using Revenue Capacity." In GLOBECOM 2015 - 2015 IEEE Global Communications Conference. IEEE, 2015. http://dx.doi.org/10.1109/glocom.2015.7417861.
Full textSingh, Mayank, Arindam Pal, Lipika Dey, and Animesh Mukherjee. "Innovation and Revenue." In CoDS COMAD 2020: 7th ACM IKDD CoDS and 25th COMAD. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3371158.3371199.
Full textAseinov, Dastan. "Autonomy of Local Governments in Taxation in Kyrgyzstan." In International Conference on Eurasian Economies. Eurasian Economists Association, 2020. http://dx.doi.org/10.36880/c12.02382.
Full textZeng, Xian-ke, and Yu-qiang Feng. "Sealed-bid multi-attribute reverse auction strategies and revenue analysis." In 2014 International Conference on Management Science and Engineering (ICMSE). IEEE, 2014. http://dx.doi.org/10.1109/icmse.2014.6930229.
Full textChun-Lin Xin, Wei-Min Ma, and Bin Liu. "Competitive revenue sharing contract." In 2008 International Conference on Machine Learning and Cybernetics (ICMLC). IEEE, 2008. http://dx.doi.org/10.1109/icmlc.2008.4620677.
Full textReports on the topic "Revenue"
Chooi, Annette. Mobilizing Revenue. Manila, Philippines: Asian Development Bank, December 2022. http://dx.doi.org/10.22617/brf220607.
Full textChooi, Annette. Mobilizing Revenue. Manila, Philippines: Asian Development Bank, March 2023. http://dx.doi.org/10.22617/brf230068.
Full textChooi, Annette. Mobilizing Revenue:. Manila, Philippines: Asian Development Bank, June 2024. http://dx.doi.org/10.22617/brf240313.
Full textAnderson, James, and J. Peter Neary. Revenue Tariff Reform. Cambridge, MA: National Bureau of Economic Research, December 2013. http://dx.doi.org/10.3386/w19752.
Full textMaron, Nancy, and Matthew Loy. Revenue, Recession, Reliance. New York: Ithaka S+R, August 2015. http://dx.doi.org/10.18665/sr.22366.
Full textCanavire-Bacarreza, Gustavo, Jorge Martínez-Vázquez, and Cristián Sepúlveda. Sub-national Revenue Mobilization in Peru. Inter-American Development Bank, March 2012. http://dx.doi.org/10.18235/0011368.
Full textRiddle, Matthew, Braeton Smith, Amanda Wagner, Amanda Savitt, and Iain Hyde. State Government Revenue Vulnerability Index and Local Government Revenue Vulnerability Index. Office of Scientific and Technical Information (OSTI), May 2021. http://dx.doi.org/10.2172/1822929.
Full textCastañeda, Luis Cesar, and Juan E. Pardinas. Sub-national Revenue Mobilization in Mexico. Inter-American Development Bank, November 2012. http://dx.doi.org/10.18235/0011423.
Full textGu, Yuanyuan, and Jhorland Ayala-García. Emigration and Tax Revenue. Banco de la República de Colombia, July 2022. http://dx.doi.org/10.32468/dtseru.312.
Full textGiovannini, Alberto, and Martha de Melo. Government Revenue from Financial Repression. Cambridge, MA: National Bureau of Economic Research, January 1991. http://dx.doi.org/10.3386/w3604.
Full text